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Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens

Urban Norway rats (Rattus norvegicus) carry several pathogens transmissible to people. However, pathogen prevalence can vary across fine spatial scales (i.e., by city block). Using a population genomics approach, we sought to describe rat movement patterns across an urban landscape and to evaluate w...

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Autores principales: Byers, Kaylee A., Booker, Tom R., Combs, Matthew, Himsworth, Chelsea G., Munshi‐South, Jason, Patrick, David M., Whitlock, Michael C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7819557/
https://www.ncbi.nlm.nih.gov/pubmed/33519965
http://dx.doi.org/10.1111/eva.13049
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author Byers, Kaylee A.
Booker, Tom R.
Combs, Matthew
Himsworth, Chelsea G.
Munshi‐South, Jason
Patrick, David M.
Whitlock, Michael C.
author_facet Byers, Kaylee A.
Booker, Tom R.
Combs, Matthew
Himsworth, Chelsea G.
Munshi‐South, Jason
Patrick, David M.
Whitlock, Michael C.
author_sort Byers, Kaylee A.
collection PubMed
description Urban Norway rats (Rattus norvegicus) carry several pathogens transmissible to people. However, pathogen prevalence can vary across fine spatial scales (i.e., by city block). Using a population genomics approach, we sought to describe rat movement patterns across an urban landscape and to evaluate whether these patterns align with pathogen distributions. We genotyped 605 rats from a single neighborhood in Vancouver, Canada, and used 1,495 genome‐wide single nucleotide polymorphisms to identify parent–offspring and sibling relationships using pedigree analysis. We resolved 1,246 pairs of relatives, of which only 1% of pairs were captured in different city blocks. Relatives were primarily caught within 33 meters of each other leading to a highly leptokurtic distribution of dispersal distances. Using binomial generalized linear mixed models, we evaluated whether family relationships influenced rat pathogen status with the bacterial pathogens Leptospira interrogans, Bartonella tribocorum, and Clostridium difficile, and found that an individual's pathogen status was not predicted any better by including disease status of related rats. The spatial clustering of related rats and their pathogens lends support to the hypothesis that spatially restricted movement promotes the heterogeneous patterns of pathogen prevalence evidenced in this population. Our findings also highlight the utility of evolutionary tools to understand movement and rat‐associated health risks in urban landscapes.
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spelling pubmed-78195572021-01-29 Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens Byers, Kaylee A. Booker, Tom R. Combs, Matthew Himsworth, Chelsea G. Munshi‐South, Jason Patrick, David M. Whitlock, Michael C. Evol Appl Special Issue Original Article Urban Norway rats (Rattus norvegicus) carry several pathogens transmissible to people. However, pathogen prevalence can vary across fine spatial scales (i.e., by city block). Using a population genomics approach, we sought to describe rat movement patterns across an urban landscape and to evaluate whether these patterns align with pathogen distributions. We genotyped 605 rats from a single neighborhood in Vancouver, Canada, and used 1,495 genome‐wide single nucleotide polymorphisms to identify parent–offspring and sibling relationships using pedigree analysis. We resolved 1,246 pairs of relatives, of which only 1% of pairs were captured in different city blocks. Relatives were primarily caught within 33 meters of each other leading to a highly leptokurtic distribution of dispersal distances. Using binomial generalized linear mixed models, we evaluated whether family relationships influenced rat pathogen status with the bacterial pathogens Leptospira interrogans, Bartonella tribocorum, and Clostridium difficile, and found that an individual's pathogen status was not predicted any better by including disease status of related rats. The spatial clustering of related rats and their pathogens lends support to the hypothesis that spatially restricted movement promotes the heterogeneous patterns of pathogen prevalence evidenced in this population. Our findings also highlight the utility of evolutionary tools to understand movement and rat‐associated health risks in urban landscapes. John Wiley and Sons Inc. 2020-07-23 /pmc/articles/PMC7819557/ /pubmed/33519965 http://dx.doi.org/10.1111/eva.13049 Text en © 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Special Issue Original Article
Byers, Kaylee A.
Booker, Tom R.
Combs, Matthew
Himsworth, Chelsea G.
Munshi‐South, Jason
Patrick, David M.
Whitlock, Michael C.
Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens
title Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens
title_full Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens
title_fullStr Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens
title_full_unstemmed Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens
title_short Using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens
title_sort using genetic relatedness to understand heterogeneous distributions of urban rat‐associated pathogens
topic Special Issue Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7819557/
https://www.ncbi.nlm.nih.gov/pubmed/33519965
http://dx.doi.org/10.1111/eva.13049
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